A single ended directional fault section identifier and fault locator for double circuit transmission lines using combined wavelet and ANN approach
• Wavelet and ANN based approach is used for fault section identification and location. • The average % error in fault location is within 0.001% which is lesser as compared to other techniques. • The proposed scheme offers primary protection to 99% of line length. • It also offers backup protection...
Ausführliche Beschreibung
Autor*in: |
Yadav, Anamika [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2015 |
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Schlagwörter: |
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Umfang: |
7 |
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Übergeordnetes Werk: |
Enthalten in: Synthesis and characterization of AsO[(W,Mo)O - Goudjil, Meriem ELSEVIER, 2023, Amsterdam [u.a.] |
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Übergeordnetes Werk: |
volume:69 ; year:2015 ; pages:27-33 ; extent:7 |
Links: |
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DOI / URN: |
10.1016/j.ijepes.2014.12.079 |
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ELV02328496X |
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520 | |a • Wavelet and ANN based approach is used for fault section identification and location. • The average % error in fault location is within 0.001% which is lesser as compared to other techniques. • The proposed scheme offers primary protection to 99% of line length. • It also offers backup protection to 99% of the adjacent forward and reverse line sections. | ||
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10.1016/j.ijepes.2014.12.079 doi GBVA2015003000026.pica (DE-627)ELV02328496X (ELSEVIER)S0142-0615(15)00004-6 DE-627 ger DE-627 rakwb eng 620 620 DE-600 540 VZ 35.90 bkl Yadav, Anamika verfasserin aut A single ended directional fault section identifier and fault locator for double circuit transmission lines using combined wavelet and ANN approach 2015 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Wavelet and ANN based approach is used for fault section identification and location. • The average % error in fault location is within 0.001% which is lesser as compared to other techniques. • The proposed scheme offers primary protection to 99% of line length. • It also offers backup protection to 99% of the adjacent forward and reverse line sections. ANN Elsevier Fault section identification Elsevier Discrete wavelet transform Elsevier Directional relaying Elsevier Fault location Elsevier Reach setting Elsevier Swetapadma, Aleena oth Enthalten in Elsevier Science Goudjil, Meriem ELSEVIER Synthesis and characterization of AsO[(W,Mo)O 2023 Amsterdam [u.a.] (DE-627)ELV009519483 volume:69 year:2015 pages:27-33 extent:7 https://doi.org/10.1016/j.ijepes.2014.12.079 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 35.90 Festkörperchemie VZ AR 69 2015 27-33 7 045F 620 |
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a single ended directional fault section identifier and fault locator for double circuit transmission lines using combined wavelet and ann approach |
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A single ended directional fault section identifier and fault locator for double circuit transmission lines using combined wavelet and ANN approach |
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• Wavelet and ANN based approach is used for fault section identification and location. • The average % error in fault location is within 0.001% which is lesser as compared to other techniques. • The proposed scheme offers primary protection to 99% of line length. • It also offers backup protection to 99% of the adjacent forward and reverse line sections. |
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• Wavelet and ANN based approach is used for fault section identification and location. • The average % error in fault location is within 0.001% which is lesser as compared to other techniques. • The proposed scheme offers primary protection to 99% of line length. • It also offers backup protection to 99% of the adjacent forward and reverse line sections. |
abstract_unstemmed |
• Wavelet and ANN based approach is used for fault section identification and location. • The average % error in fault location is within 0.001% which is lesser as compared to other techniques. • The proposed scheme offers primary protection to 99% of line length. • It also offers backup protection to 99% of the adjacent forward and reverse line sections. |
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A single ended directional fault section identifier and fault locator for double circuit transmission lines using combined wavelet and ANN approach |
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